Disputation: Summaya Mumtaz
Doctoral candidate Summaya Mumtaz at the Department of informatics, Faculty of Mathematics and Natural Sciences, is defending the thesis Hierarchy-based Similarity Measures and Embeddings — Supporting Machine Learning by Knowledge for the degree of Philosophiae Doctor.
The PhD defence and trial lecture will be fully digital and streamed directly using Zoom. The host of the session will moderate the technicalities while the chair of the defence will moderate the disputation.
Ex auditorio questions: the chair of the defence will invite the audience to ask ex auditorio questions either written or oral. This can be requested by clicking 'Participants -> Raise hand'.
Title: "Integrating logic and probabilities with neural networks"
Main research findings
The real-world application of Artificial Intelligence/machine learning techniques is challenging. Most of the standard machine learning approaches, depend heavily on large amounts of historical data. However, in real-world complex use cases, the data vary across several dimensions which makes it challenging to find a sufficient amount of quality data. Particularly, in low-resource domains, not enough training data is available, which affects the machine learning model’s performance. In many disciplines a significant amount of prior knowledge about the domain is available, often in the form of a taxonomy or a hierarchy. For instance, a disease hierarchy in the medical domain that classifies diseases into different groups based on similar symptoms. We have experimented in three domains by adding domain knowledge: recommending hydrocarbon reserves in the oil and gas industry, grouping similar words in natural language and patient mortality prediction in health care domain. Our research has shown that addition of domain knowledge (taxonomy) in the given scenarios where little training data is available, can improve the performance of the prediction task.
- Associate Professor Robert Hoehndorf, Computer, Electrical and Mathematical Sciences & Engineering Division, Computational Bioscience Research Center, King Abdullah University of Science and Technology, Kingdom of Saudi Arabia
- Tenure-Track Assistant Professor Dagmar Gromann, Department for Translation Studies, University of Vienna, Austria
- Professor Geir Kjetil Sandve, Department of Informatics, University of Oslo, Norway
- Professor Martin Giese, Department of Informatics, University of Oslo, Norway
- Professor Christos Dimitrakakis, Department of Informatics, University of Oslo, Norway
Chair of defence
- Associate Professor Ingrid Chieh Yu, Department of Informatics, University of Oslo, Norway
Candidate contact information: email
Contact information to Department: Anniken R. Birkelund